Campus Units
Industrial and Manufacturing Systems Engineering, Statistics
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
2014
Journal or Book Title
Computational Statistics & Data Analysis
Volume
71
First Page
520
Last Page
529
DOI
10.1016/j.csda.2013.02.004
Abstract
A variety of existing symmetric parametric models for 3-D rotations found in both statistical and materials science literatures are considered from the point of view of the “uniform-axis-random-spin” (UARS) construction. One-sample Bayes methods for non-informative priors are provided for all of these models and attractive frequentist properties for corresponding Bayes inference on the model parameters are confirmed. Taken together with earlier work, the broad efficacy of non-informative Bayes inference for symmetric distributions on 3-D rotations is conclusively demonstrated.
Rights
© 2014. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Copyright Owner
Elsevier, B.V.
Copyright Date
2014
Language
en
File Format
application/pdf
Recommended Citation
Qiu, Yu; Nordman, Danial J.; and Vardeman, Stephen B., "One-sample Bayes inference for symmetric distributions of 3-D rotations" (2014). Industrial and Manufacturing Systems Engineering Publications. 137.
https://lib.dr.iastate.edu/imse_pubs/137
Included in
Industrial Engineering Commons, Statistics and Probability Commons, Systems Engineering Commons
Comments
This is a manuscript of an article published as One-sample Bayes inference for existing symmetric distributions on 3-d rotations. Computational Statistics and Data Analysis, 2014, Vol. 71, pp. 520-529, DOI:10.1016/j.csda.2013.02.004. With Yu Qiu and Dan Nordman.